Rajiv Jain, Brian Kersmanc & Surdarshan Murthy

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Transcript Question 1: Why have fears of a bubble in financial markets surfaced? Andrew: Fears of a bubble have intensified this year amid skyrocketing valuations of AI and tech stocks. Major indices like the S&P 500 and Nasdaq have hit repeated all time highs largely propelled by a handful of mega-cap growth stocks with an AI theme. The major US and global indices are capitalisation weighted, which means that they own more of the bigger companies than the smaller ones. As a result these broad indices have significant concentration risk in just a few stocks. For the S&P 500, nearly 30% of the index is allocated to just five companies and nearly 40% is allocated to just ten. If the reality of AI does not live up to the hype and some of those giant tech stocks fall in value, they can have a major negative impact on the return of the entire index. Sunil: Well we've just passed the three year anniversary of the release of ChatGPT, and in that time every business associated with building out the AI infrastructure has gone in one direction, and that is up. After several years of that, people are fairly asking how far can this run and how big can this be? A common theme you see from prior market bubbles is a narrowing of the market. So narrower and narrower, smaller number of companies driving the returns and the returns increasingly being driven by a single theme, in this case AI. So it's a fair question at this point, three years in, where most of the stock market has not done very much but a narrow slice of the market has done incredibly well. It's a fair question to ask are we in a bubble? Question 2: Does the investment case for AI remain strong? Andrew: AI is an exciting new technology that should deliver incredible productivity enhancements across the entire economy. However, the investment case for most AI stocks is very questionable. First, AI is massively capital intensive, requiring hundreds of billions of dollars of investment in data centres. Compared to that enormous spending, there is comparatively little revenue being generated by the AI service providers. Thus, AI companies are burning through cash at an incredible rate. Furthermore, investors in AI companies have to pay high valuations for the right to own these cash burning businesses. It is more than possible that AI could be a revolutionary technology and a smashing success and still AI companies today could be terrible investments. In fact, that's exactly what happened during the tech bubble of 1999. The internet was a revolutionary technology and a smashing success, and yet all the internet darlings from the tech bubble were disastrous investments for the next 5 to 10 years after that bubble burst. Sunil: We believe the long-term investment case for AI remains very strong despite growing questions around whether or not the markets are currently in a bubble. Ultimately, when there's a paradigm shift for any new technology, you will see winners, losers, over-building, over-investment. Our view though is that if the underlying technology is something that brings real efficiency and real benefit to the end user, then the companies that are enabling that paradigm shift should do quite well over time. Our belief is that those are the types of businesses that we are invested in, and as long as the underlying value creation is there, then the underlying investment case remains. Question 3: How big a threat is China to US AI dominance? Andrew: China potentially poses a significant and growing threat to US AI dominance, but it does not seem like an immediate or existential threat yet. Currently, the US holds the lead in AI innovation. China seems to be excelling at cost efficiency. The US benefits from superior private investment, top-tier compute access and breakthrough research. But export controls have accelerated China's efforts, and they have narrowed the gap in model performance. As with any technology, the situation is very fluid and could change with each new breakthrough in AI. Sunil: China and the United States are clearly engaged in a battle for economic supremacy, and AI is simply the next front in that war. Both countries view it as a matter of national security. Our view is a little bit more nuanced and that we don't see it as a zero sum game. Progress in the United States and progress in China does not necessarily have to have a negative impact on the other. So ultimately, we think that AI will go down a similar path to many other areas of tech which is what we would call a two stack world, a Chinese version and an American version. One issue that the Chinese face that is structural and is long term in nature is that some of the underlying capital equipment that is required to actually manufacture advanced semiconductors only comes from Western based businesses, so that will continue to be a structural headwind to Chinese AI development. But it's one that they've shown that they're quite adept at overcoming with innovation. Question 4: How are you managing tech-related risks? Andrew: At Lyrical we look to invest in stocks that have three key traits: value, quality and analysability. We do not hold any of the hyped AI stocks because they do not possess these traits. First, we believe AI stocks are incredibly expensive and so they do not meet our valuation criteria by a wide margin. Second, AI companies are incredibly capital intensive and do not meet our quality criteria that prefers capital light business models. Lastly, AI technology is rapidly evolving and difficult, if not impossible, to predict, and so AI stocks do not meet our analysability criteria. That said, while we do not own any of the hyped AI stocks, we do own many other stocks that are benefiting from AI spending, including power producers and data centre suppliers. We also own companies that are benefiting from AI technology to improve their businesses. If AI stocks truly are in a bubble, our portfolio, we believe, is well positioned to avoid the painful losses that would occur if that bubble were to pop. Sunil: Given the duration and the narrowness of the bull market that we’re in, it’s a fair question to ask how are we managing the tech-related risks in our portfolio? And really we look at those kinds of risks through two lenses. One is a criteria lens at the individual company level. We, by design, want to own businesses that we believe are leaders at what they do and that we believe have durable, competitive moats around the franchises. We think that that is one of the most powerful risk management tools at our disposal. Secondly, the second lens is portfolio construction, and that's about managing the aggregate weight and exposure to different industries and in this case, technology and balancing out that exposure appropriately with exposure in other areas such as consumer, life sciences and industrial businesses.